Innovations in Drone Collision Prevention Systems

(Summary) Controlling unmanned vehicles to prevent collisions and reduce user burden when multiple vehicles are operated. It provides autonomous control for commercial off-the-shelf unmanned vehicles via an add-on controller that receives user inputs and generates modified control signals to instruct the vehicles to follow pre-determined routes. The controller analyzes the user inputs and extracts the intended maneuvering commands while discarding velocity changes. To avoid collisions, the routes are generated by a server based on sensor data and deconflicting with other vehicles.

(Summary) Machine learning can be used to guide unmanned aerial vehicles (UAVs) and other platforms around obstacles without expensive imaging systems. The approach involves training ML models to generate guidance information like object locations based on time-of-arrival (TOA) data from sensors. This avoids the computational expense of processing images to identify obstacles in real-time on board the platform.

(Summary) Flight control system for unmanned aerial vehicles that enables safe passing of nearby aircraft. The system detects nearby aircraft and determines if passing is possible based on their trajectories and airspace conditions. If passing is possible, it controls the drone to perform a passing maneuver at a safe distance from the other aircraft.

(Summary) System for mid-air collision avoidance and traffic control between unmanned aerial platforms with different priority levels. The system involves CAS (collision avoidance system) units on each platform that intermittently transmit their locations. Higher-priority platforms can receive these transmissions and calculate collision risks. If the risk is high, the higher priority platform CAS unit generates and transmits steering commands to the lower priority platform to avoid a collision.

(Summary) A recovery system for unmanned aerial vehicles (UAVs) to prevent catastrophic crashes and damage when a UAV experiences critical failures. The recovery system has a parachute housed in an ejectable pod mounted on the UAV. Sensors monitor flight status and triggers like loss of power or communication. When a critical failure is detected, the pod is ejected, and the parachute deploys to slow the UAV's descent and prevent crashing.

(Summary) A drone control system that prevents collisions and enables filming subjects from different angles. The controller uses predefined rails of positions for the drone to follow, along with mathematical modeling. The rails are virtual paths that prevent collisions and give coordinated shots. The drone minimizes a cost function that includes variables like contour error and lag error to optimize rail following.

(Summary) Collision avoidance for vehicles like unmanned aerial vehicles (UAVs) using modulated light beacons from objects like buildings. The buildings emit light beacons modulated with useful signals carrying object information. UAVs have event-based vision sensors that detect changes in beacon brightness and estimate distances to avoid collisions. This enables collision avoidance without external infrastructure or RF systems.

(Summary) Detecting obstacles and targets using passive infrared sensors on drones and vehicles to enable efficient collision avoidance and tracking. PIR sensors receive heat signals from obstacles like humans, calculate distances, and determine whether to take collision avoidance maneuvers. The PIR signals also allow for the recognition of targets like humans for tracking.

(Summary) Dynamic path planning allows vehicles like aircraft to safely navigate an area with obstacles and other vehicles. It models the area as sub-areas and calculates a summation value for each sub-area based on proximity to obstacles. Sub-areas meeting a rule are connected to form the vehicle's path through the area. As obstacles move or new ones appear, the path is recomputed in real time to avoid them.

(Summary) A drone with flexible arms that can be selectively bent using integrated actuators. The arms are made of lightweight, semi-rigid materials like inflatable structures. They have electromagnetic actuator cells that can bend the arms when activated. The drone's control system can selectively activate the actuators to flex the arms in different configurations. This allows the drone to reposition its rotors to avoid obstacles and crashes. The flexible arm design enhances maneuverability and crash resilience compared to rigid drone arms.